نتایج جستجو برای: adaptive neural fuzzy inference system anfis

تعداد نتایج: 2710765  

Journal: :iran agricultural research 2013
jamshid piri hosein ansari

evaporation, as a major component of the hydrologic cycle, plays a key role in water resources development and management in arid and semi-arid climatic regions. although there are empirical formulas available, their performances are not all satisfactory due to the complicated nature of the evaporation process and the data availability. this paper explores evaporation estimation methods based o...

This paper employs Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict water level that leads to flood in coastal areas. ANFIS combines the verbal power of fuzzy logic and numerical power of neural network for its action. Meteorological and astronomical data of Santa Monica, a coastal area in California, U. S. A., were obtained. A portion of the data was used to train the ANFIS network, wh...

2009
Meysam Alizadeh Roy Rada Akram Khaleghei Ghoshe Balagh Mir Mehdi Seyyed Esfahani

This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for USD/JPY exchange rates forecasting. Previous work often used time series techniques and neural networks (NN). ANFIS can be used to better explain solutions to users than completely black-box models, such as NN. The proposed neurofuzzy rule based system applies some technical and fundamental indexes as input variables. In o...

2012
J. Amani R. Moeini

Reinforced concrete beam; Shear strength; Artificial neural network; Adaptive neuro-fuzzy inference system; Iranian concrete institute code; American concrete institute code. Abstract In this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are used to predict the shear strength of Reinforced Concrete (RC) beams, and the models are compared with A...

Journal: :journal of mining and environment 2013
saeed mojeddifar hojatollah ranjbar hossain nezamabadipour

the main problem associated with the traditional approach to image classification for the mapping of hydrothermal alteration is that materials not associated with hydrothermal alteration may be erroneously classified as hydrothermally altered due to the similar spectral properties of altered and unaltered minerals. the major objective of this paper is to investigate the potential of a neuro-fuz...

Journal: :JNW 2014
Jian Zhang

In complex manufacturing, the system parameters have dynamic and nonlinear characters. Existing parameters setting methods show low efficiency and accuracy, and some setting experience accumulated in engineering practice can not be fully used. Therefore, an online parameter setting method with improved adaptive neuro-based fuzzy inference model is proposed in this paper. The advantages of ANFIS...

  Storing the electrical energy in large scale is impossible. So, it is necessary to identify the factors affecting the electricity demand. Researchers have used different methods to forecast the future demand of electricity, among them intelligent methods and fuzzy based methods are more popular. Since ANFIS structure is based on researcher’s experience about phenomenon, the created structure ...

2011
Himanshu Chaudhary Rajendra Prasad

In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) method based on the Artificial Neural Network (ANN) is applied to design an Inverse Kinematic based controller forthe inverse kinematical control of SCORBOT-ER V Plus. The proposed ANFIS controller combines the advantages of a fuzzy controller as well as the quick response and adaptability nature of an Artificial Neural Network (AN...

2013
Devendra S. Chaudhari

314 Abstract— Neuro-Fuzzy systems are hybrid intelligent systems which combine features of both paradigmsfuzzy logic and artificial neural networks. Adaptive Neuro Fuzzy Inference System (ANFIS) is one of such architecture which is widely used as solution for various real world problems. This paper describes development of an ANFIS model for FPGA implementation. Model can be realized with hardw...

Ahmad Reza Mostafa Gharabaghi, Ehsan Delavari, Mohmmad Reza Chenaghlou,

Wave height as well as water depth at the breaking point are two basic parameters which are necessary for studying coastal processes. In this study, the application of soft computing-based methods such as artificial neural network (ANN), fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS) and semi-empirical models for prediction of these parameters are investigated. Th...

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